scholarly journals Bayesian Group Chain Sampling Plan for Poisson Distribution with Gamma Prior

2022 ◽  
Vol 70 (2) ◽  
pp. 3891-3902
Author(s):  
Waqar Hafeez ◽  
Nazrina Aziz ◽  
Zakiyah Zain ◽  
Nur Azulia Kamarudin
Keyword(s):  
Poisson Distribution ◽  
Sampling Plan

Designing optimal double sampling plan using the weighted Poisson distribution

2015 ◽  
Vol 33 (1) ◽  
pp. 62-77 ◽  
Author(s):  
Venugopal Haridoss ◽  
Kandasamy Subramani
Keyword(s):  
Poisson Distribution ◽  
Design Methodology ◽  
Sampling Plan ◽  
Shop Floor ◽  
Double Sampling ◽  
Content Type ◽  
Final Inspection ◽  
The Given

Purpose – The purpose of this paper is to present the optimal double sampling attribute plan using the weighted Poisson distribution. Design/methodology/approach – For the given AQL and LQL, sum of producer’s and consumer’s risks have been attained. Based on the weighted Poisson distribution, the sum of these risks has been optimized. Findings – In the final inspection, the producer and the consumer represent the same party. So, the sum these two risks should be minimized. In this paper, the sum of risks has been tabulated using the weighted Poisson distribution for different operating ratios. These tabulated values are comparatively less than the sum of risks derived using Poisson distribution. Originality/value – The sampling plan presented in this paper is particularly useful for testing the quality of finished products in shop floor situations.

scholarly journals Designing of Chain Sampling Plan under Gamma-Poisson Distribution

2019 ◽  
Vol 9 (1S4) ◽  
pp. 711-714
Keyword(s):  
Poisson Distribution ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sampling Plan ◽  
Conditional Sampling ◽  
Optimal Parameters ◽  
Sampling Plans ◽  
Operating Characteristic Curve

In this manuscript, we discuss the designing procedure of chain sampling plan which is known as one of the conditional sampling plans under gamma-Poisson distribution. We determine the optimal parameters namely, number of items to be chosen for inspection from the lot and number of preceding lots to be considered in order to dispose the current lot by specifying two points on the operating characteristic curve, which is the usual designing approach of sampling plan. The procedure which is used to execute the proposed plan is provided and comparison is made among the proposed plan and existing sampling plans performance.

scholarly journals Implication of Production and Monitoring Techniques in Bayesian Single Sampling Plan using Gamma-Zero Inflated Poisson Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 10110-10119
Keyword(s):  
Poisson Distribution ◽  
Sampling Procedure ◽  
Sampling Plan ◽  
Manufacturing Industries ◽  
Optimal Plan ◽  
Bayesian Sampling ◽  
Single Sampling Plan ◽  
Zip Model ◽  
Random Fluctuations ◽  
Selection Of

This article explores the problem of investigate Single Sampling Plan (SSP) by attributes under Bayesian theory and illuminate its importance methodology in manufacturing industries. The modern technological advancements and well monitoring of the production process are facilitate to enhance the standard of product. In such situation products are not meeting the specified quality standards is a rare phenomenon. However, random fluctuations in producing processes might lead some merchandise to an imperfect quality. It has been assumed that the number of defects per unit of product follows a Zero Inflated Poisson distribution (ZIP) and the Gamma distribution is the conjugate prior to the average number of non-conformities per item. This article proposed a new sampling procedure as Bayesian Single Sampling plan (BSSP) using Gamma-Zero Inflated Poisson (G-ZIP) distribution. Necessary tables for the selection of optimal plan parameters and numerical illustrations were made for this sampling plan. Furthermore, the applicability and usefulness of the proposed Bayesian sampling plan under the G-ZIP model have been demonstrated by a few examples and comparisons were made with other sampling plans.

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